Jobs at Latitude AI

Lead and mentor an engineering team developing production-grade deep learning and computer vision models for autonomous driving. Oversee roadmap execution, model deployment, multi-sensor fusion, spatio-temporal modeling, software quality, validation, and collaboration with motion planning, localization, infrastructure, and hardware teams. Guide models from research prototypes through real-time vehicle deployment while ensuring latency, reliability, and safety-critical performance.

Performs exploratory data analysis, extracts and transforms data from BigQuery using complex SQL, builds production data models with dbt, investigates data quality issues, and supports data integrations. Uses Git and GitHub for version control and code review, Linux for scripting and file management, and Jira and Atlassian automation for workflow management.

Performs quality assurance on labeled autonomous vehicle sensor data, identifies error trends and discrepancies, tests tools and workflows, mentors team members, prepares clarification materials, provides feedback to third-party teams, and escalates quality concerns. The role requires sustained attention to detail, clear reporting, strong communication, and the ability to analyze large data samples using workplace productivity and workflow tools.

Develop and improve large-scale simulation and resimulation cloud frameworks for autonomous vehicle testing. Write efficient, tested Python applications, integrate AWS/GCP services, benchmark system performance, build dashboards, manage vehicle-log indexing and dataset coverage, and support extensible metrics workflows. Collaborate with autonomy and testing teams to improve usability, documentation, scalability, and developer self-service across cloud and on-premise environments.

Provide Tier I and Tier II enterprise IT support, manage tickets and incidents, deploy and refresh devices, build and provision servers, support Zoom Rooms and company events, and assist with onboarding and offboarding. The role requires desktop support expertise across macOS and Linux, networking and hardware troubleshooting, collaboration tools, configuration management, and strong communication across distributed teams.

Leads the Scalable Machine Learning team and owns technical strategy for data generation, orchestration, distributed training, and shared ML infrastructure. Responsibilities include managing engineers, setting multi-quarter roadmaps, coordinating GPU scheduling and cloud infrastructure, advancing MLOps practices, influencing peer teams, delivering multi-organization initiatives, and maintaining high reliability across shared systems.

Designs and leads safety-critical embedded firmware for automotive hardware safety and power systems. Responsibilities include architecting safe-state strategies, power sequencing, thermal monitoring, watchdog systems, low-level drivers, diagnostic frameworks, and HALs for ARM-based SoCs. The role requires FreeRTOS or SafeRTOS expertise, ISO 26262 ASIL-B/C knowledge, register-level debugging, hardware-software safety integration, code reviews, failure analysis, and mentoring engineers.

Develop spatio-temporal machine learning models for automated driving, collaborate with experts on algorithm design, and ensure production-level implementation of perception systems.